Construction Machinery & Heavy Transportation Equipment Data: Production, Trade, Fleets and Resale · Head-to-head
USGS Mineral Commodity Summaries (Construction Aggregates) vs California CARB Heavy-Duty Vehicle Emissions Inventory Data
Which construction machinery & heavy transportation equipment data: production, trade, fleets and resale data fits your job: USGS Mineral Commodity Summaries - Construction aggregates, or California CARB - heavy-duty vehicle emissions & inventory data. API, files, or your warehouse. Daily, weekly, or hourly.
USGS Mineral Commodity Summaries - Construction aggregates (crushed stone, sand & gravel)
California CARB - heavy-duty vehicle emissions & inventory data
Where the fields line up
No shared field names. These two answer different questions.
| Field | USGS Mineral Commodity Summaries - Construction aggregates | California CARB - heavy-duty vehicle emissions & inventory data |
|---|---|---|
Sold or used by producers | documented | not in this set |
Recycled material | documented | not in this set |
Imports for consumption | documented | not in this set |
Consumption, apparent | documented | not in this set |
Price, average unit value | documented | not in this set |
Employment, quarry and mill | documented | not in this set |
Net import reliance | documented | not in this set |
Leading States | documented | not in this set |
Tariff item number | documented | not in this set |
Import sources | documented | not in this set |
emissions_inventory | not in this set | documented |
vehicle_population | not in this set | documented |
What each contains
Pick by fit, not by loyalty.
| USGS Mineral Commodity Summaries - Construction aggregates | California CARB - heavy-duty vehicle emissions & inventory data | |
|---|---|---|
| Documented fields | 10 | 6 field families |
| Definition confidence | Verified during research | Inferred |
| Signature fields | `Sold or used by producers`; `Recycled material`; `Imports for consumption`; `Consumption, apparent`; `Price, average unit value`; `Employment, quarry and mill`; `Net import reliance`; `Leading States`; `Tariff item number`; `Import sources` | `emissions_inventory`; `vehicle_population`; `zev_credit_balance`; `model_year`; `manufacturer`; `gvwr_threshold` |
| Shared concepts | Period stamp anchoring each observation | Period stamp anchoring each observation (`model_year`) |
| Units carried | Million metric tons; dollars per metric ton; headcount; percent of apparent consumption | Pollutant-specific emission estimates; vehicle counts; credit balances; GVWR thresholds in pounds and horsepower |
| Named entities | None - companies and quarries appear only as counts (~1,400 companies, ~3,500 quarries) | Yes - `manufacturer` strings such as Rivian in ACT credit summaries |
| Overlap verdict | Structural overlap only: both stamp observations with a period. Tonnage economics versus fleet-and-emissions regulation. | — |
What each does better
the USGS aggregates record
No other record in this pairing touches dollars or jobs.
Trade dependence is quantified, not implied. Import sources breaks origin shares across a trailing five years (Canada 42 percent, Mexico 23 percent in the documented example) and Net import reliance sits beside apparent consumption as a percentage - about 1 percent for these commodities, meaning domestic quarries supply nearly everything. A tariff item number even carries the HTS line with its rate, such as 2517.10.0055.
the CARB record
It reaches individual vehicles and named manufacturers. The USGS chapters stop at national totals and never name an operator; CARB's ACT credit summaries hang on manufacturer strings - Rivian appears in the documented example with a model-year credit balance - and the compliance programs classify real fleets by gvwr_threshold: over 8,500 lbs under Advanced Clean Fleets, over 14,000 lbs under Clean Truck Check, off-road diesel equipment of 25 hp or greater. That is asset-level resolution the aggregates chapters cannot approach.
Geographic depth runs to the neighborhood. Coverage is statewide California with community-level heavy-duty inventories down to census block group since January 2026, against USGS's national grain with producing states named only in narrative.
It carries the technology signal. Emissions inventories by pollutant, fleet populations by vehicle category drawn from registration data, and manufacturer ZEV sales requirements together say where powertrains are heading - context that feeds directly into emission standards database comparisons and equipment planning.
One honest caveat from the research notes: bulk machine-readable extracts of the compliance-reporting systems were not confirmed during verification, and some EMFAC2025 outputs await federal approval for certain regulatory uses - check the documentation before building on those cells.
Where they're equivalent
More than the subjects suggest. Both publishers are government agencies speaking with regulatory or statistical authority rather than vendor marketing. Both resolve to an annual clock as their finest published rhythm - USGS editions arrive each January, CARB model releases land roughly annually to biennially with the fleet database refreshed each year. Both are national-scale records anchored to one country's economy: United States totals for USGS, California totals for CARB, with neither offering a county-level cut in the core tables. And both document their structure explicitly enough to be cataloged here at 8/10 and 7/10 on Datadory's rubric - above water in an industry slice whose scores run from 4 to 9.
Where they part company is tense and unit. USGS reports what happened to physical tonnage; CARB reports what must happen to vehicles and their emissions. One speaks in million metric tons, the other in pollutants, populations and credits.
The verdict
Verdict: sample both, pick by fit - they answer different halves of the same equipment-economy question, and neither subsumes the other.
Accept the trade - national totals only, five-year windows, no operator names. That shape suits competitive intel product teams use cases mapping where material demand pulls equipment sales.
Take California CARB heavy-duty vehicle emissions & inventory data if your question is about the machines: which truck and off-road fleets face which weight-class rules, how many vehicles populate each category, which manufacturers hold ZEV credits for which model years. Accept the trade - one state's frame, inferred field definitions, compliance detail behind reporting portals. That shape fits data scientists use cases modeling fleet turnover and electrification.
Rule of thumb: if the noun in your question is a ton, start with USGS; if it is a truck, start with CARB. More pairings live in the construction machinery & heavy transportation equipment data hub.
Sample both, pick by fit. See USGS Mineral Commodity Summaries - Construction aggregates · See California CARB - heavy-duty vehicle emissions & inventory data
Or take both in one feed
Yes - stacked in sequence they cover both ends of a construction-equipment demand model. Read the USGS chapters first for the volume signal: how many tons of crushed stone and sand & gravel moved last year, at what unit value, from how many quarries and pits. Aggregate tonnage hauled is the workload that drives truck duty cycles, so it sets the denominator for any fleet-turnover question. Then read CARB for the constraint side: which vehicle categories and weight classes the rules reach, what the inventory says about current emissions and populations, and which manufacturers are banking ZEV credits against future model years.
Two cautions straight from the records. First, there is no join key: USGS rows key on commodity and year, CARB rows on vehicle category, model year and geography, so document the assumption linking tons hauled to vehicles active - see vehicle registration statistics for the usual bridge layer, and FHWA Highway Statistics for the registration counts that make it concrete. Second, respect geography and tense: national annual tonnage against statewide inventories keyed by model year means any combined figure is an allocation, not an observation.
Datadory ships either record alone or both merged onto one delivery calendar, normalized to their documented field dictionaries with sample rows attached for validation - delivered daily, weekly, or hourly, your call. Or take both in one feed.
API, files, or your warehouse. Daily, weekly, or hourly.
Fair questions
Is USGS Mineral Commodity Summaries better than CARB heavy-duty emissions data?
Better at different jobs, scored 8/10 versus 7/10. CARB wins the machine economy: emissions inventories by pollutant, fleet populations by category, and manufacturer ZEV credit balances by model year.
Do the two datasets cover the same ground anywhere?
Structurally, barely. Both stamp observations with a period and both publish through government agencies, but their subjects never intersect - USGS documents tons, dollars and workers in aggregates, while CARB documents pollutants, vehicle populations and credits. They complement rather than compete, which is why the verdict is sample both, pick by fit.
Which dataset covers more geography?
USGS by breadth, CARB by depth. The aggregates chapters summarize all 50 states with ranked leaders such as Texas, Pennsylvania and Florida, while CARB covers exactly one state - but resolves heavy-duty activity to community level and census block group, finer than anything in the USGS tables.
Can either dataset tell me about specific companies?
Only indirectly. USGS never names an operator: it counts them - about 1,400 companies running 3,500 quarries in crushed stone, about 3,400 over 6,500 pits in sand and gravel. CARB goes further, naming manufacturers in Advanced Clean Trucks credit summaries, with Rivian among the documented examples holding model-year credit balances.
Can Datadory deliver both datasets together?
Yes. Either record arrives alone or merged onto one delivery calendar, normalized to its documented field dictionary with sample rows attached for validation. Name the commodities, states, vehicle categories and model years when you request the sample and it lands pre-cut - delivered daily, weekly, or hourly, your call.